U.S. patent application number 16/859322 was filed with the patent office on 2021-10-28 for battery state estimation using injected current oscillation.
This patent application is currently assigned to GM GLOBAL TECHNOLOGY OPERATIONS LLC. The applicant listed for this patent is GM GLOBAL TECHNOLOGY OPERATIONS LLC. Invention is credited to Justin Bunnell, Charles W. Wampler, Meixian Wang, Yue-Yun Wang, Houchun Xia.
Application Number | 20210336462 16/859322 |
Document ID | / |
Family ID | 1000004829335 |
Filed Date | 2021-10-28 |
United States Patent
Application |
20210336462 |
Kind Code |
A1 |
Wang; Meixian ; et
al. |
October 28, 2021 |
BATTERY STATE ESTIMATION USING INJECTED CURRENT OSCILLATION
Abstract
A method for estimating a state of a battery pack using a
controller having battery state estimator (BSE) logic includes
receiving or delivering a constant baseline current via the battery
pack. Current oscillations having time-variant frequency content
are selectively injected into the baseline current via the
controller in response to a predetermined condition. The baseline
current and the current oscillations combine to form a final
current. The method includes estimating a battery parameter via the
BSE logic concurrently with the current oscillations to generate an
estimated battery parameter, and estimating the present state of
the battery pack via the controller using the estimated battery
parameter. An electrical system includes a rotary electric machine
that is electrically connected to and driven by the battery pack,
and a controller configured to execute the method.
Inventors: |
Wang; Meixian; (Troy,
MI) ; Wang; Yue-Yun; (Troy, MI) ; Xia;
Houchun; (Troy, MI) ; Bunnell; Justin;
(Northville, MI) ; Wampler; Charles W.;
(Birmingham, MI) |
|
Applicant: |
Name |
City |
State |
Country |
Type |
GM GLOBAL TECHNOLOGY OPERATIONS LLC |
Detroit |
MI |
US |
|
|
Assignee: |
GM GLOBAL TECHNOLOGY OPERATIONS
LLC
Detroit
MI
|
Family ID: |
1000004829335 |
Appl. No.: |
16/859322 |
Filed: |
April 27, 2020 |
Current U.S.
Class: |
1/1 |
Current CPC
Class: |
G01R 31/389 20190101;
H02J 7/0048 20200101; G01R 31/396 20190101; B60L 53/62 20190201;
B60L 15/20 20130101; B60L 58/12 20190201; G01R 31/3842 20190101;
H02J 7/0068 20130101 |
International
Class: |
H02J 7/00 20060101
H02J007/00; G01R 31/389 20060101 G01R031/389; G01R 31/3842 20060101
G01R031/3842; G01R 31/396 20060101 G01R031/396; B60L 58/12 20060101
B60L058/12; B60L 53/62 20060101 B60L053/62; B60L 15/20 20060101
B60L015/20 |
Claims
1. A method for estimating a present state of a battery pack using
a controller having battery state estimator (BSE) logic, the method
comprising: receiving or delivering a constant baseline current via
the battery pack; selectively requesting injection of current
oscillations having time-variant frequency content into the
constant baseline current, via the controller in response to a
predetermined condition, wherein the constant baseline current and
the current oscillations combine to form a final current;
estimating a battery parameter of the battery pack via the BSE
logic concurrently with the current oscillations to thereby
generate an estimated battery parameter; and estimating the present
state of the battery pack via the controller using the estimated
battery parameter to thereby generate an estimated battery state of
the battery pack.
2. The method of claim 1, wherein the BSE logic includes a Kalman
filter.
3. The method of claim 1, further comprising: controlling powerflow
to or from the battery pack via the controller using the estimated
battery state.
4. The method of claim 3, wherein selectively requesting the
injection of the current oscillations into the constant baseline
current includes requesting a constant charging current, via the
controller, from an offboard charging station as the constant
baseline current, and wherein controlling powerflow to or from the
battery pack includes charging the battery pack using the final
current.
5. The method of claim 3, wherein selectively requesting the
injection of the current oscillations into the constant baseline
current includes selectively controlling an ON/OFF state of an
electrical load connected to the battery pack while receiving or
delivering the constant baseline current to thereby create the
current oscillations, and wherein controlling the powerflow to or
from the battery pack includes discharging the battery pack to the
electrical load.
6. The method of claim 3, wherein selectively requesting the
injection of the current oscillations into the constant baseline
current includes selectively requesting, from an offboard charging
station, a series of constant charging currents each having a
different frequency content to thereby create the current
oscillations, and wherein controlling the powerflow to or from the
battery pack using the estimated battery state includes charging
the battery pack using the final current.
7. The method of claim 1, wherein selectively requesting the
injection of the current oscillations into the constant baseline
current includes communicating a charging request from the
controller to an offboard smart charger that is configured to
detect a requirement of the battery pack for the final current, and
that is configured to transmit the final current to the battery
pack as a charging current.
8. The method of claim 1, wherein estimating the battery parameter
includes estimating an ohmic resistance, an impedance, and/or an
open-circuit voltage of the battery pack.
9. The method of claim 1, wherein a frequency of the current
oscillations is less than about 1 Hz, and the constant baseline
current has a frequency of less than about 0.01 Hz.
10. The method of claim 1, wherein the current oscillations include
a pseudo-random binary signal having a time-variant frequency.
11. The method of claim 1, wherein the current oscillations include
a pulse width modulation signal or a pulse density modulation
signal having a time-variant frequency.
12. The method of claim 1, wherein the current oscillations are a
sequence of chirp signals.
13. The method of claim 1, wherein the predetermined condition
includes a threshold covariance or an estimated error value from
the BSE logic.
14. The method of claim 1, wherein the predetermined condition
includes a calibrated duration over which the constant baseline
current remains constant prior to injection of the current
oscillations.
15. An electrical system comprising: a battery pack; a rotary
electric machine that is electrically connected to and driven by
the battery pack; and a controller configured to estimate a present
state of a battery pack using battery state estimator (BSE) logic,
wherein the controller is configured to: determine, via the BSE
logic, a frequency content of a constant baseline current delivered
to or from the battery pack, wherein the constant baseline current
has a frequency of less than about 0.01 Hz; selectively request an
injection of current oscillations into the constant baseline
current in response to a predetermined condition, wherein the
constant baseline current and the current oscillations combine to
form a final current, and wherein the current oscillations have a
frequency in a range of between about 0.1 Hz and 1 Hz; estimate a
battery parameter of the battery pack via the BSE logic
concurrently with the current oscillations to thereby generate an
estimated battery parameter, wherein the estimated battery
parameter is an ohmic resistance, an impedance, and/or an
open-circuit voltage of the battery pack; estimate the present
state of the battery pack using the estimated battery parameter as
an estimated battery state; and control powerflow from or to the
electric machine respectively to or from the battery pack using the
estimated battery state.
16. The electrical system of claim 15, wherein the BSE logic
includes a Kalman filter.
17. The electrical system of claim 16, wherein the predetermined
condition includes a covariance value, and wherein the estimated
battery parameter is a regressed ohmic resistance of the battery
pack.
18. The electrical system of claim 15, wherein the controller is
configured to selectively request the injection of the current
oscillations into the constant baseline current by requesting a
constant charging current from an offboard charging station as the
constant baseline current, and to control charging of the battery
pack as the powerflow using the final current.
19. The electrical system of claim 15, wherein the current
oscillations include a pseudo-random binary signal, a pulse width
modulation signal, a pulse density modulation signal, and/or a
sequence of chirp signals.
20. The electrical system of claim 15, further comprising one or
more road wheels connected to the rotary electric machine.
Description
INTRODUCTION
[0001] The present disclosure relates to the real-time estimation
of modeled battery parameters and battery states of a multi-cell
battery pack. Accurate estimation allows an associated controller
to effectively and efficiently control a myriad of different power
usage and utilization decisions during battery charging,
steady-state, and discharging operating modes. The present
disclosure thus lends itself to the real-time control of
electrified powertrains, powerplants, robots, mobile platforms, and
other types of electrical systems in which improved battery
parameter and state estimation accuracy is desirable.
[0002] Ongoing measurements of the various responses to a given
input are not always possible or practicable in a deterministic
system, which in turn often necessitates the use of system models
and response estimation based on such models. In a typical
high-energy battery pack, for instance, such as a lithium-ion
traction battery pack of an electric or hybrid electric motor
vehicle, voltage and temperature are periodically measured and
estimated as responses to electrical current. Different voltage
states may be modeled, including equilibrium potential, hysteresis
effects-based voltage responses, voltage drops due to ohmic
resistance, voltage drops due to battery pack dynamics, e.g.,
double-layer and/or diffusion voltage, etc. Each of the exemplary
voltage responses may be described in a model using an algebraic or
differential function, or by using a convolution integral. The
above-noted voltage responses in particular influence key battery
state estimates such as state of charge (SOC) and state of power
(SOP)/power capability. As a result, equivalent circuit models are
typically used in conjunction with adaptive battery state
estimation (BSE) logic in order to estimate voltage responses and
other battery parameters.
[0003] As will be appreciated by those of ordinary skill in the
art, a battery cell resting under open-circuit conditions, given
sufficient time, will eventually settle at an equilibrium voltage
referred to in the art as the cell's open-circuit voltage (OCV).
Ideally, the OCV of a given battery cell is unique for each SOC
independently of whether the battery cell was charging or
discharging immediately prior to switching to an open-circuit
condition, and independently of the magnitude of the battery
current. While OCV is accurately ascertained in a battery pack in
an off state for an extended duration, a key challenge presents
itself when attempting to perform battery state estimations of a
battery pack that is actively charging or discharging, particularly
in dynamically changing operating environments.
[0004] In lithium-ion batteries in particular, a non-linear
relationship exists between OCV and SOC. In hybrid electric and
battery electric vehicles, for instance, BSE logic in the form of a
programmed algorithm may reference an available OCV curve to help
estimate SOC in real-time. Alternatively, SOC may be tracked over
time from an initial SOC value using a procedure referred to in the
art as Coulomb counting. Other BSE logic variations seek to balance
voltage-based estimates with available Coulomb counting-based
estimates in order to produce a composite estimate.
SUMMARY
[0005] A method and an associated system are disclosed herein that
are intended to improve upon available battery parameter and state
estimation accuracy in an electrical system having a multi-cell
battery pack. As part of the disclosed solution, a controller is
programmed to execute instructions embodying the present method,
with the controller doing so using battery state estimation (BSE)
logic and current control logic as described herein. The controller
uses an application-specific equivalent circuit model to accurately
estimate and regress one or more relevant battery parameters.
Representative non-limiting regressed battery parameters within the
scope of the present disclosure include open-circuit voltage (OCV),
ohmic resistance (R-ohmic), and impedance of the battery pack, with
SOC and SOP being representative battery states that may be
estimated from such battery parameters using the disclosed
approach.
[0006] As understood in the art, certain battery parameters enjoy
greater predictive value than other battery parameters during
higher-frequency current inputs, particularly when estimating SOC
and SOP/power capability of a battery pack. As a result, it is
desirable to optimize estimation accuracy for such battery
parameters. Ohmic resistance is one such parameter. Ohmic
resistance, which is generally defined as the apparent internal
resistance of a battery pack and the resistance of the various
electrical conductors used in the battery pack's construction.
Ohmic resistance tends to manifest as an instantaneous cell voltage
response to changes in battery current, is particularly significant
to SOP/power capability estimations.
[0007] It is recognized herein as a basis for the present solution
that battery state estimators configured to regress battery
parameters, which may include Extended Kalman Filters, Sigma-Point
Kalman Filters, recursive least-squares regression techniques, and
the like, may experience insufficient levels of input signal
variation/excitation under certain operating conditions.
Insufficient excitation in turn may lead to inaccurate estimation
results. Noise present in a signal measurement environment, such as
measured electrical current, voltage, and temperature, may result
in a low signal-to-noise ratio. When insufficient frequency content
is present in the input signals being furnished to the resident BSE
logic, the predicted battery parameters may tend to drift, with the
battery parameters possibly rising or falling in a monotonic manner
as a result. The present solution is therefore intended to address
this problem by selectively modifying a constant baseline current
of the battery pack, i.e., a charging or discharging current, by
purposefully injecting time-variant frequency content in the form
of current oscillations into the baseline current.
[0008] In a particular embodiment, a method is provided for
estimating a state of a battery pack via a controller having BSE
logic configured to regress a set of battery parameters. The method
includes receiving or outputting a constant baseline current via
the battery pack. The method also includes selectively requesting
the injection/addition of time-variant frequency content in the
form of current oscillations to the constant baseline current, with
such a request occurring via the controller. This action is
accomplished in response to a predetermined condition that is
itself indicative of the above-noted insufficiency of frequency
content. The constant baseline current and the current oscillations
combine to form a final current.
[0009] The method in this particular embodiment includes estimating
a battery parameter of the battery pack via the BSE logic to
thereby provide an estimated battery parameter, and thereafter
estimating the present state of the battery pack as an estimated
battery state using the estimated battery parameter.
[0010] The BSE logic may include an extended Kalman filter or other
Kalman filter formulation.
[0011] Selectively requesting the injection of the current
oscillations into the constant baseline current may include
requesting a constant charging current, via the controller, from an
offboard charging station as the constant baseline current, and
wherein controlling powerflow to or from the battery pack includes
charging the battery pack using the final current. Alternatively,
selectively requesting the injection of the current oscillations
into the constant baseline current includes selectively controlling
an ON/OFF state of an electrical load connected to the battery pack
while receiving or delivering a constant baseline current to
thereby create the current oscillations. Controlling the powerflow
to or from the battery pack in this instance may include
discharging the battery pack to the electrical load.
[0012] As another alternative, selectively requesting the injection
of the current oscillations into the constant baseline current may
include selectively requesting, from an offboard charging station,
a series of constant charging currents each having a different
frequency content to thereby create the current oscillations, and
wherein controlling the powerflow to or from the battery pack using
the estimated battery state includes charging the battery pack
using the final current, or communicating a charging request from
the controller to an offboard smart charger. Such a smart charger
may be configured to detect a requirement of the battery pack for
the final current, and that is configured to transmit the final
current to the battery pack as a charging current.
[0013] The battery parameter may include an ohmic resistance, an
impedance, and/or an open-circuit voltage of the battery pack in
various embodiments.
[0014] In an exemplary embodiment, the frequency of the current
oscillations may be less than about 1 Hz, and the constant baseline
current may have a frequency of less than about 0.01 Hz. The
current oscillations may include a pseudo-random binary signal
having a time-variant frequency, or pulse width modulation or pulse
density modulation signal having a time-variant frequency, or a
sequence of chirp signals.
[0015] In a possible embodiment, the predetermined condition may
include a threshold covariance or an estimated error value from the
BSE logic, or a duration over which the constant baseline current
remains constant prior to injection of the current
oscillations.
[0016] An electrical system is also disclosed herein that,
according to an exemplary embodiment, includes a rotary electric
machine that is electrically connected to and driven by the battery
pack, and a controller configured to estimate a present state of a
battery pack using the BSE logic noted above. In an exemplary
embodiment, the controller is configured to determine, via the BSE
logic, a frequency content of a constant baseline current delivered
to or from the battery pack, wherein the constant baseline current
has a frequency of less than about 0.01 Hz. The controller is also
configured to selectively request an injection of current
oscillations into the constant baseline current in response to a
predetermined condition, with the constant baseline current and the
current oscillations combining to form a final current. In a
non-limiting embodiment, the current oscillations have a frequency
in a range of between about 0.1 Hz and 1 Hz, e.g., within .+-.5% or
.+-.10% of the stated values or an otherwise reasonable tolerance
thereof, and to estimate a battery parameter of the battery pack
via the BSE logic concurrently with the current oscillations to
thereby generate an estimated battery parameter. The estimated
battery parameter in this embodiment is an ohmic resistance, an
impedance, and/or an open-circuit voltage of the battery pack.
[0017] The controller is further configured to estimate the present
state of the battery pack using the estimated battery parameter as
an estimated battery state, and to thereafter control, using the
estimated battery state, a powerflow from or to the electric
machine respectively to or from the battery pack. One or more road
wheels may be connected to the rotary electric machine.
[0018] The above summary is not intended to represent every
possible embodiment or every aspect of the present disclosure.
Rather, the foregoing summary is intended to exemplify some of the
novel aspects and features disclosed herein. The above features and
advantages, and other features and advantages of the present
disclosure, will be readily apparent from the following detailed
description of representative embodiments and modes for carrying
out the present disclosure when taken in connection with the
accompanying drawings and the appended claims.
BRIEF DESCRIPTION OF THE DRAWINGS
[0019] FIG. 1 is a schematic illustration of an example electrical
system having a battery pack and a controller, with the latter
including battery state estimation (BSE) logic configured to
regress battery parameters and estimate a state of the battery
pack.
[0020] FIG. 2 is a time plot of regressed ohmic resistance
(vertical axis) versus time (horizontal axis) in the absence of the
present teachings.
[0021] FIGS. 3A and 3B are time plots of regressed ohmic resistance
and percentage state of charge depicted on the respective vertical
axes and time depicted on the respective horizontal axes for a
representative charging cycle.
[0022] FIGS. 4A and 4B are time plots of regressed ohmic resistance
and percentage state of charge depicted on the respective vertical
axes and time depicted on the respective horizontal axes for a
representative discharging cycle.
[0023] FIG. 5 is a schematic flow diagram depicting charging
control logic usable by the controller depicted in FIG. 1 when
selectively injecting frequency content into a constant baseline
current in accordance with the present teachings, with nominal
current oscillation depicted on the vertical axis and time depicted
on the horizontal axis.
[0024] FIG. 6 is a time plot depicting a representative final
current on the vertical axis and time depicted on the horizontal
axis.
[0025] FIG. 7 is a time plot showing a representative application
of the present method, with magnitude of a final current depicted
on the vertical axis and time depicted on the horizontal axis.
[0026] The present disclosure is susceptible to modifications and
alternative forms, with representative embodiments shown by way of
example in the drawings and described in detail below. Inventive
aspects of this disclosure are not limited to the particular forms
disclosed. Rather, the present disclosure is intended to cover
modifications, equivalents, combinations, and alternatives falling
within the scope of the disclosure as defined by the appended
claims.
DETAILED DESCRIPTION
[0027] Referring to the drawings, wherein like reference numbers
refer to like components, FIG. 1 depicts an exemplary vehicle 10
having an onboard electrical system 12, a controller (C) 50, and a
set of road wheels 11, with the latter being in rolling contact
with a road surface 20. The vehicle 10 is illustrative of just one
possible application of the present teachings, and is used herein
solely for the purpose of illustrative consistency. Those of
ordinary skill in the art will appreciate that the present
teachings may be extended to a wide variety of dynamic systems and
devices such as but not limited to motor vehicles, watercraft,
aircraft, rail vehicles, mobile platforms, robots, powerplants, or
other systems having a similar electrical system 12.
[0028] The electrical system 12 in the non-limiting embodiment of
FIG. 1 includes a high-energy/high-voltage multi-cell battery pack
13 (B.sub.HV) whose various battery parameters and states are
estimated by the controller 50 as described herein. By way of
example and not limitation, the battery pack 13 may have a
lithium-ion battery chemistry, and may be capable of outputting at
least 18V and as much as 400V or more depending on the
configuration.
[0029] In some embodiments of the vehicle 10, the electrical system
12 includes a polyphase rotary electric machine (M.sub.E) 15 such
as a motor-generator unit. In such an embodiment, motor torque
(arrow T.sub.M) from the energized electric machine 15 may be
transmitted to one or more of the road wheels 11 and/or to another
coupled load. A power inverter module (PIM) 17 is disposed between
the battery pack 13 and the electric machine 15 and configured, in
response to pulse width modulation or other suitable high-speed
switching control signals and operation of phase-associated
semiconductor switches (not shown), to invert a DC voltage (VDC)
from the battery pack 13 and thereby generate a polyphase/AC
voltage (VAC) for energizing stator windings (not shown) of the
electric machine 15. Likewise, operation of the PIM 17 may convert
an AC voltage (VAC) from the electric machine 15 into a DC voltage
(VDC) suitable for recharging the battery pack 13.
[0030] The battery pack 13 noted generally above includes a
plurality of electrochemical battery cells 14. Four such battery
cells 14 are individually labeled C1, C2, C3, and C4 in FIG. 1 for
added clarity and simplicity. The actual number of battery cells 14
used in the construction of the battery pack 13 is
application-specific and depends on the energy requirement of
electrical loads or devices powered by the battery pack 13, such as
but not limited to the rotary electric machine 15. Although shown
schematically for illustrative simplicity and clarity, the electric
machine 15 may be coupled to the road wheels 11 directly or via
intervening gear arrangements and drive axles to power the electric
machine 15 in its capacity as an electric traction motor and
thereby propel the vehicle along a road surface 20.
[0031] Powerflow to or from the electrical system 12 may be managed
in real-time by the controller 50, e.g., when configured as a
battery system manager or another control device or devices, with
the controller 50 regulating ongoing operation of the electrical
system 12 via output control signals (arrow CCo). According to the
present strategy, the controller 50 employs battery state
estimation (BSE) logic 52, an application-specific equivalent
circuit model (K-EQ) 54, and sensors 16 that collectively measure
and communicate input signals to the controller 50 and its resident
BSE logic 52. Such input signals in the illustrated configuration
include cell voltages (arrow V.sub.C), battery current (arrow I),
and battery temperature (arrow T). The input signals may be
determined locally within each battery cell 14 or measured
collectively at the level of the battery pack 13 and
back-calculated or estimated from such levels in different
embodiments.
[0032] The controller 50, which may be configured as part of a
larger battery management system or as a separate computer device
or network of such devices, includes a processor (P), e.g., a
microprocessor or central processing unit, memory (M) in the form
of read only memory, random access memory,
electrically-programmable read only memory, etc., a high-speed
clock, analog-to-digital and digital-to-analog circuitry,
input/output circuitry and devices, and appropriate signal
conditioning and buffering circuitry. The strategies described
below may be encoded as machine-readable instructions collectively
referred to herein as a method 100.
[0033] In executing the present method 100, the controller 50
automatically derives the battery's present operating state,
including a bulk state of charge and state of power of the battery
pack 13. The controller 50 does so using the BSE logic 52 with the
assistance of the equivalent circuit model 54, the latter of which
generally models behavior of the battery pack 13 using, as circuit
elements, the battery voltage, a hysteresis voltage source, ohmic
resistance, battery and/or cell voltage, resistance, and
capacitance, etc., and accounts for factors such as surface charge
on the various battery cells 14. Depending on the complexity of the
equivalent circuit model 54, the equivalent circuit model 54 may
also account for solid-state diffusion voltage effects and other
higher and/or lower frequency voltage effects occurring within the
constituent battery cell(s) 14 of the battery pack 13.
Collectively, the various voltage effects are added or subtracted
from the open-circuit voltage of the battery cell(s) 14.
[0034] The particular configuration of the equivalent circuit model
54 is based on the particular application and construction of the
battery pack 13 and thus may have a wide variety of constructions.
Non-limiting representative example constructions usable as the
equivalent circuit model 54 may be found, for instance, in U.S.
Pat. No. 9,575,128 entitled "Battery State-Of-Charge Estimation For
Hybrid and Electric Vehicles Using Extended Kalman Filter
Techniques" issued on Feb. 21, 2017, U.S. Pat. No. 6,639,385
entitled "State of Charge Method and Apparatus" issued on Oct. 28,
2003, and U.S. Pat. No. 7,324,902 entitled "Method and Apparatus
for Generalized Recursive Least-Squares Process for Battery State
of Charge and State of Health" issued on Jan. 29, 2008, which are
hereby incorporated by reference in their entireties.
[0035] State of charge and state of power estimations are adapted
in real-time using the BSE logic 52. In a possible embodiment, the
BSE logic 52 may include an extended Kalman filter and additional
current control logic 55 (OSC), with an example of the latter
depicted in FIG. 5, to improve overall estimation accuracy in the
face of a constant baseline current flowing into or out of the
battery pack 13 of FIG. 1. As will be appreciated by those of
ordinary skill in the art, an extended Kalman filter formulation is
typically used to treat system models having the following general
form:
x.sub.k=f(x.sub.k,u.sub.k)+w.sub.k
z.sub.k=h(x.sub.k)+n.sub.k
where w.sub.k and n.sub.k are noise factors. For the representative
BSE logic 54 of the present disclosure, the input is
u.sub.k=i.sub.k=current to or from the battery pack 13. The
measured value is z.sub.k=V.sub.k, which in this instance is the
cell voltage of a battery cell 14 or a pack voltage of the battery
pack 13 shown schematically in FIG. 1. x.sub.k is the state vector
including battery parameters to be estimated by the BSE logic
52.
[0036] As understood in the art, the estimated state of the battery
pack 13 and other deterministic systems is the smallest vector
summarizing the system's collective past. Alternatives to the
extended Kalman filter formulation within the scope of the
disclosure include but are not limited to Sigma-Point Kalman
Filters and the like, as well as formulations that do not follow
Kalman filter formalism, e.g., recursive least-squares regression,
particle filters, etc. The extended Kalman filter, which
effectively uses a single point and partial derivatives of the
associated equivalent circuit model 54, is therefore just one
possible approach to regressing battery parameters within the scope
of the disclosure.
[0037] Still referring to FIG. 1, the present solution enabled by
the controller 50 and its resident BSE logic 52 is intended to
operate in electrical systems ordinarily having a constant baseline
current, such as the exemplary electrical system 12 and battery
pack 13. The baseline current contemplated herein may be a charging
current supplied by an offboard charging station (V.sub.CH) 25 that
is connectable to the vehicle 10, e.g., via a charging port 10C, to
initiate a charging cycle of the battery pack 13. The charging
station 25 may deliver an AC or DC charging current depending on
the configuration of the offboard charging station 25, or the
baseline current may be a battery current supplied by the battery
pack 13 to power the electric machine 15, a resistive element,
and/or another electrical load. In some embodiments the charging
station 25 may be adapted for use as a smart charger 25S, and thus
equipped with associated processors, logic, sensors, and other
requisite hardware and software for communicating with the
controller 50 to determine the charging requirements of the battery
pack 13.
[0038] As used herein, the term "constant" with respect to the
baseline current refers to an electrical current having very low
frequency content, e.g., less than about 0.01 Hz or less than about
0.005 Hz in different embodiments. The term "very low" is to be
understood relative to the sampling speed of the controller 50 when
implementing the BSE logic 52. Such sampling speed may be less than
about 1-10 Hz in an exemplary embodiment. As the offboard charging
station 25 may be optionally embodied as a DC fast-charger capable
of rapidly charging the battery pack 13 with a DC charging voltage
and associated DC charging current, a DC current waveform
epitomizes constancy within the scope of present disclosure, and
thus the constant baseline current treated herein may be a DC
charging current or an alternating current (AC) charging current
having the above-defined very low frequency content.
[0039] As noted above, the controller 50 of FIG. 1 is configured
for estimating battery parameters and a present state of a battery
pack 13 using the BSE logic 52. In an embodiment, the method 100
includes receiving or delivering a constant baseline current via
the battery pack 13 from or to a load, respectively. As described
below with reference to FIGS. 2-7, the method 100 includes
selectively requesting injection of time-variant frequency content
as current oscillations, e.g., a dither signal, into the constant
baseline current. This occurs by operation of the controller 50
using the current control logic 55.
[0040] With respect to the current control logic 55, and referring
briefly to FIG. 5, the baseline current (i.sub.BL) 42 and the
current oscillations (i.sub.OSC) 44, shown as varying in a
nominal/representative .+-.3 A range, sum to combine and form a
final current (i.sub.F) 46. The non-limiting exemplary embodiment
of FIG. 5 depicts the current oscillations 44 as a Pseudo-Random
Binary Signal or PRBS oscillation. Alternative embodiments of the
current oscillations 44 exist, including a frequency-varied signal
such as a pulse-width modulation or pulse-density modulation
signal, a sequence of chirp signals, or other varied frequency
signals configured to generate sufficient excitation to the BSE
logic 52. While the frequency of the current oscillations 44 may
vary with the application or within a given implementation, the
frequency content should be high relative to the constant baseline
current, e.g., a range of about 0.1-1 Hz, or anywhere in such a
range, e.g., discrete frequencies of 0.1 Hz, 0.5 Hz, or 1 Hz.
[0041] According to the present method 100, a battery parameter of
the battery pack 13 such as regressed R-ohmic, capacitance, or OCV
is automatically estimated via the BSE logic 52 of FIG. 1
concurrently with injection of the current oscillations 44, with
"injection" as used herein referring to a summed combination or
overlay of the current oscillations (i.sub.OSC) 44 respectively
with or onto the constant baseline current 42 as indicated by a
summation node (+). Temporarily, the resultant waveform, i.e., the
final current (i.sub.F) 46, an exemplary embodiment of which is
shown in FIG. 6 for a representative period of t(s)=600 seconds, is
provided to or by the battery pack 13. The controller 50 of FIG. 1
may then estimate the present state of the battery pack 13 using
the estimated battery parameter.
[0042] Referring to FIG. 2, a potential vulnerability of the BSE
logic 52 of FIG. 1, absent the present teachings and use of the
current control logic 55 of FIG. 5, is that of the possible
degradation of estimation accuracy due to a lack of sufficient
frequency content in the constant baseline current 42. The constant
baseline current 42, shown for simplicity in FIG. 2 as a step
signal and referenced on the vertical axis as I(A), is exemplary of
the very low frequency content described above. A representative
battery parameter that could be estimated by the BSE logic 52 is a
regressed ohmic resistance/R-ohmic (trace 30), which is abbreviated
R-.OMEGA. and shown on the other vertical axis of FIG. 2. In the
illustrated trace 30, regressed ohmic resistance is monotonically
increasing. A discrepancy between estimated battery parameters when
charging the battery pack 13 of FIG. 1 using a constant charging
current and when discharging the battery pack 13 during a typical
drive cycle could reduce the overall accuracy of SOC and SOP
estimates, with a possible result of such degraded accuracy
indicated in FIG. 2 as the monotonically increasing ohmic
resistance.
[0043] The potential vulnerability in the form of suboptimal
estimation accuracy may be better understood with reference to
FIGS. 3A, 3B, 4A, and 4B. Trace 130 of FIG. 3A is similar to FIG. 2
in its depiction of a monotonically increasing R-ohmic value of the
type that may result from a sustained constant charging current,
e.g., from the offboard charging station 25 shown in FIG. 1. In
FIG. 3B, for proper calibration of the controller 50 and the
resident BSE logic 52, the difference between trace "SOC.V" 35,
i.e., the SOC % as regressed by the BSE logic 52, and trace 34
"SOC.Ahr" provided from Coulomb counting methods ideally should be
minimal, e.g., less than 5%. In reality, it is difficult to tune
onboard calibrations to accurately meet this requirement during
constant current charging conditions, as indicated by the variation
between traces 34 and 35 in FIG. 3B. Indeed, following a sustained
constant charging current, it may take an extended amount of time
for R-ohmic and other estimated battery parameters to regress to a
normal or expected range during a subsequent drive cycle, for
instance taking as much as twenty minutes to more than an hour
depending on the initial regressed R-ohmic value at the start of
the drive cycle.
[0044] FIGS. 4A and 4B illustrate the effect on the example R-ohmic
battery parameter in the face of a non-constant battery current,
with FIGS. 4A and 4B representing a response in regressed R-ohmic
from the BSE logic 52 when discharging the battery pack 13 during
an exemplary drive/discharging cycle of the vehicle 10 shown in
FIG. 1. While battery current during a discharging event such as a
drive cycle of the vehicle 10 is typically non-constant, e.g., due
to rapid variations in output torque request, at times the vehicle
10 may cruise at a fixed speed for an extended duration. The
observed effect on estimated or regressed R-ohmic, i.e., trace 230
of FIG. 4A, likewise leads to convergence of traces 34 and 35
relative to the constant current conditions of FIG. 3B. This is
illustrated using corresponding traces 134 and 135 in FIG. 4B,
which is indicative of increased estimation accuracy of regressed
R-ohmic.
[0045] As an example application, the battery pack 13 of FIG. 1 may
be operated at a constant baseline current, with the regressed
R-ohmic value monotonically increasing as shown in FIG. 3A. When
the controller 50 of FIG. 1 has determined based on a predetermined
condition indicative of insufficient frequency content in the
baseline current, the controller 50 requests the injection of the
time-variant oscillation 44 (FIG. 5). As a non-limiting
illustration, should a constant charge current of 58-amps be
provided to the battery pack 13 and the predetermined condition be
detected or present indicative of insufficient frequency content in
the charge current, the controller 50 may respond by requesting
injection of the time-variant oscillations 44 from the current
control logic 55 of FIG. 1, such that the charge current is caused
to vary sufficiently from 58-amps, such as by oscillating between
48-amps and 58-amps at a frequency of 1 Hz. sensors
[0046] The predetermined conditions used to trigger frequency
content enhancement may depend to some extent on the particular
formulation used to implement the BSE logic 52. For example, a
timer of the controller 50 may be initiated at the onset of a
constant baseline current, with a threshold elapsed time being used
as the predetermined condition. Other embodiments of the
predetermined condition may include a threshold variation in the
baseline current, such as variance in current calculated over a
time window, cruise control system status, plug-in charge status, a
threshold change in temperature, SOC, and/or voltage of the battery
pack 13, etc.
[0047] With respect to covariance, Kalman formulations provide a
covariance or an approximation thereof, as will be appreciated by
those skilled in the art. The magnitude of covariance may be used
as the predetermined condition using extended Kalman filters or
other Kalman formulations of the BSE logic 52. For example,
particle filters keep track of statistical distribution by
randomized sampling of the associated model, e.g., the equivalent
circuit model 54 of FIG. 1. As an appropriate trigger for
selectively injecting the constant baseline current 42 of FIG. 7
with additional frequency content of the current oscillations 44,
parameter fitting techniques could be subjected to a statistical
analysis, e.g., via analytic formula or by brute-force methods.
Using "brute force" approaches, one can take a measured signal,
perturb it with noise at the level of accuracy of the sensors 16 of
FIG. 1, and then re-compute the relevant battery parameters. By
repeating such a process many times, a cloud of parameter values is
generated that indicates the covariance. Sigma-Point Kalman filters
by comparison compute covariance from just a few selected perturbed
points, while the extended Kalman filter uses a single point and
partial derivatives of the equivalent circuit model 54.
[0048] In a general sense, signal-to-noise ratio (SNR) is used to
inform the injection triggering decision. A good measure of SNR in
the example extended Kalman filter embodiment of the BSE logic 52
would be to compare the estimate of the battery parameter to the
estimate of its standard deviation. If x is the column vector of
battery parameters, the extended Kalman filter produces an
estimate, x*, and a covariance matrix,
C=.epsilon.{(x-x*)(x-x*).sup.T}, where .epsilon.{ } is the
expectation. Then, for the i.sup.th battery parameter, |x.sub.i*|/
{square root over (C.sub.ii)} is a measure of how accurately the
extended Kalman filter thinks it is measuring that parameter. In
the case of ohmic resistance, for instance, k may serve as the
index for R-ohmic. Taking the reciprocal, we might initiate current
oscillation when
C k .times. k x k * = .sigma. .function. ( R .times. o .times. h
.times. m .times. i .times. c ) R .times. o .times. h .times. m
.times. i .times. c ##EQU00001##
exceeds a specified value, with .sigma. representing standard
deviation, i.e., the square-root of variance. Similarly, the
controller 50 could decide to situationally inject the time-variant
current oscillation 44 whenever another battery parameter loses
accuracy by a similar criterion.
[0049] From calibration, the controller 50 is provided with a rough
value of the battery parameters, which could be used instead of the
estimate, which as noted herein may become unreliable. The
calibration values are typically stored in tables, e.g., with
R-ohmic stored in a table indexed by % SOC and temperature. Letting
X.sub.i(SOC,T) be the look-up value of parameter x.sub.i, the
controller 50 could set a value of {square root over
(C.sub.ii)}/X.sub.i(SOC,T) where injection of the time-variant
current oscillation is triggered. An EKF may be implemented in
square-root form, in which case it gives a matrix S such that
C=S.sup.TS. Thus, the controller 50 may calculate C.sub.ii from S
in some embodiments. Instead of a ratio, the controller 50 could
alternatively trigger on {square root over (C.sub.ii)}.
[0050] In the equivalent circuit model 54 of FIG. 1, ohmic
resistance is a higher-frequency impedance. At a representative 100
ms sample rate (i.e., 10 Hz), regressed R-ohmic corresponds to the
impedance of the battery pack 13 at frequencies above about 1 Hz.
If the baseline current 42 has no frequency content above 0.1 Hz,
for instance, there is a lack of information available to
accurately estimate R-ohmic, causing the estimate to become
unreliable and drift. Other battery parameters model
lower-frequency effects, and thus do not require as high of a
frequency content to fit. However, lower-frequency battery
parameters may likewise drift if the frequency content of the
baseline current is very low. In the absence of sufficient
excitation, the uncertainty in a given battery parameter grows with
time. Thus, the predetermined condition within the scope of the
disclosure may extend to the above-noted and other criteria for
judging that too much time has elapsed since a significant current
oscillation, which in turn would trigger a request for the currents
oscillation 44 of FIG. 7.
[0051] FIG. 7, which is best understood in conjunction with FIG. 5,
is a time plot 45 schematically depicting the final current
(I.sub.F) 46 of FIG. 5 in amps (A) with intermittently-injected
time-variant current oscillations 44. As explained above, the final
current 46 is the sum of the constant baseline current 42 and the
current oscillations 44, and therefore the constant baseline
current 42 equals the final current 46 of FIG. 5 when the current
oscillations 44 are discontinued.
[0052] Commencing at t.sub.0 with receipt or delivery of the
constant baseline current 42 via the battery pack 13 shown in FIG.
1, the controller 50 selectively requests injection of the current
oscillations 44 into the constant baseline current 42 at about
t.sub.1 in response to a predetermined condition, various options
for which are set forth above. This injection continues until
t.sub.2. The decision as to precisely when to commence and
discontinue injection of a given current oscillation 44 may be made
by the controller 50 using the predetermined condition(s), a few
examples of which are set forth below. The controller 50 of FIG. 1
estimates ohmic resistance, impedance, and OCV and/or other battery
parameters of the battery pack 13 via the BSE logic 52. Estimation
occurs concurrently with injection of the current oscillations 44,
as well as at other times. The controller 50 may thereafter
estimate the present state of the battery pack 13 using the
estimated battery parameter(s).
[0053] As depicted in FIG. 7 for a representative charging cycle in
which constant current charging commences at t.sub.0 and continues
until t.sub.7, and in which constant voltage charging commences at
t.sub.7 and continues until t.sub.8 (as trace 142), the selective
injection of the current oscillations 44 need not be continuous. In
the illustrated embodiment, for instance, the controller 50
requests injection of the current oscillations 44 between t.sub.1
and t.sub.2, t.sub.3 and t.sub.4, and t.sub.5 and t.sub.6. The
frequency content of the current oscillations 44 may be the same at
each instance of injection, or it may be different as shown.
[0054] Various embodiments exist that are suitable predetermined
conditions for triggering injection of the current oscillations 44,
with the embodiment possibly depending on the formulation of the
BSE logic 52 as noted above. By way of example and not limitation,
the predetermined condition may include a covariance or an
estimated error value from the BSE logic 52 indicative of a level
of confidence in estimation accuracy of the battery parameter. The
predetermined condition may include a calibrated duration over
which the constant baseline current 42 remains constant prior to
injection of the current oscillations 44, with such an alternative
relying on the use of a timer, for instance of the controller 50.
Other values may be used as predetermined conditions/triggering
conditions, such as but not limited to a predefined temperature
differential, Amp-hour differential, and/or covariance differential
of the battery pack 13.
[0055] Additionally, the offboard charging station 25 of FIG. 1 may
have different configurations and capabilities which informs the
range of options afforded the controller 50 for implementing the
present teachings. For example, during a charging operation in
which the offboard charging station 25 is connected to the battery
pack 13/vehicle 10 and is actively charging the battery pack 13,
the controller 50 may request a particular constant charging
current, e.g., 10-amps, for a brief duration. Such a charging
current may be immediately followed by a different constant
charging current, e.g., 8-amps, followed again by another 10-amp
charging current and so forth. In this illustrative example, the
duration and possibly magnitude of each successive charging current
may be selected by the controller 50 to produce the requisite
frequency content for exciting the BSE logic 52.
[0056] The offboard charging station 25 may be configured as the
smart charger 25S shown in FIG. 1, i.e., a station programmed for
and thus capable of communicating wirelessly or over hardwired
transfer conductors with the controller 50 to determine the
charging requirement and capabilities of the battery pack 13. In
such an embodiment, the controller 50 may request injections of the
current oscillations 44 into the constant baseline current 42 by
communicating a charging request to the smart charger 25S, with the
smart charger 25S detecting a requirement of the battery pack 13
for the final current 46. The smart charger 25S in such an
embodiment responds by transmitting the final current 46 to the
battery pack 13 as a charging current, with the composition of the
final current 46 at a given time instant being either the constant
current 42 alone or a combination of the constant current 42 and
the time-variant current oscillations 44.
[0057] As yet another embodiment, the battery pack 13 could receive
or output a constant current, e.g., 10A. To provide the requisite
frequency content, the controller 50 could selectively discharge
1-2A of current, such as by selectively activating a resistive load
or resident electrical component of the vehicle 10. The particular
load may vary with the application, and thus may range from
sufficiently high-current devices as a battery or RESS heater, air
conditioning compressor, etc. Selective discharge of the battery
pack 13 may occur in this embodiment during active drive states of
the vehicle 10, for instance while cruising at a constant velocity,
or during active charging states of the vehicle 10.
[0058] The method 100 set forth above is thus intended to improve
the accuracy of state and parameter estimates of typical battery
state estimators. The output of a battery state estimator will tend
to grow with higher frequency content in its input. However,
low-frequency content leads to reduced output, such as is the case
with DC charging current or other currents varying by less than
0.01 Hz. If the output has not exceeded a given threshold for too
long, the controller 50 could request injection of the
above-described current oscillations 44. For parameters associated
to lower-frequency effects, some implementations may use separate
triggers or predetermined conditions, each with its own time
constant. Essentially, the present approach selectively adds
sufficient frequency content to ensure a given signal rises above
an associated noise level, and thereby addresses a vulnerability in
common BSE approaches used with motor vehicles and other systems
having the battery pack 13 described above. These and other
benefits will be readily appreciated by those of ordinary skill in
the art in view of the forgoing disclosure.
[0059] While some of the best modes and other embodiments have been
described in detail, various alternative designs and embodiments
exist for practicing the present teachings defined in the appended
claims. Those skilled in the art will recognize that modifications
may be made to the disclosed embodiments without departing from the
scope of the present disclosure. Moreover, the present concepts
expressly include combinations and sub-combinations of the
described elements and features. The detailed description and the
drawings are supportive and descriptive of the present teachings,
with the scope of the present teachings defined solely by the
claims.
* * * * *